Literature DB >> 31121440

Measuring perceived mistreatment across diverse social groups: An evaluation of the Everyday Discrimination Scale.

Catherine E Harnois1, João L Bastos2, Mary E Campbell3, Verna M Keith4.   

Abstract

RATIONALE: Research assessing the health-related consequences of perceived discrimination depends upon high quality measures of perceived discrimination. The Everyday Discrimination Scale (EDS) is among the most frequently used instruments to assess perceptions of discrimination in general, as well as specific types of discrimination (e.g., based on race/ethnicity or age). While numerous studies attest to its validity and reliability for racial/ethnic minority groups, no existing study has examined its psychometric equivalence across gender, age, or socio-economic groups. This study fills this gap. HYPOTHESIS: We hypothesize that because social hierarchies of race/ethnicity, age, gender and class have different histories and are differently organized and institutionalized in contemporary United States, racial/ethnic, age, gender, and education-based groups differ in the types of discrimination they experience and perceive. As a result, the EDS may not be equivalent across these social groups.
METHOD: We test this hypothesis by analyzing data from the 2015 US Texas Diversity Study (N=1,049), a telephone survey of English- and Spanish-speaking adults. We examine two forms of the EDS - one focusing on discrimination regardless of attribution and one focusing specifically on discrimination attributed to respondents' race/ethnicity.
RESULTS: Multi-group confirmatory factor analyses revealed that neither version of the scale generates estimates of discrimination that can be meaningfully compared across all racial/ethnic, age, gender, and education-based groups.
CONCLUSIONS: Our results urge caution when drawing comparisons of perceived discrimination across diverse social groups based on the EDS and point to avenues for future scale development.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Age; Bias; Gender; Psychometrics; Racism; Social Discrimination; Socio-economic Status; United States.

Year:  2019        PMID: 31121440     DOI: 10.1016/j.socscimed.2019.05.011

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


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